35results about How to "Reduce bandwidth consumption" patented technology

The invention introduces an unlimited multi-terminal connection Bluetooth audio system based on a broadcast technology, and aims to break through the limitation of a traditional Bluetooth audio system on the equipment connection number and tone quality transmission. By utilizing the technology, the system supports seamless connection with an infinite number of playing terminals, the application range is greatly expanded, and the connection flexibility is improved. The LC3 audio decoding technology integrated in the system significantly improves the quality and efficiency of audio transmission, and ensures excellent auditory experience. Besides, the equipped digital power amplifier and the Bluetooth main control chip allow a user to flexibly process and optimize audio output of each channel through an advanced frequency division control technology, and support independent or combined sound channel output setting. The design of the system not only adapts to household and commercial environments, but also can be widely applied to scenes such as public speech and multi-room music playing, the functionality and operation convenience of the audio system are greatly improved, and the new possibility of the Bluetooth audio technology in multiple scenes is developed.

The invention relates to the technical field of traffic control, and discloses an expressway traffic prediction method and system based on a cloud side end, and the method comprises the steps: configuring data collection equipment of an expressway, and constructing a whole-region road sensing network of the expressway; configuring edge computing nodes of the expressway at the key hub, and obtaining a lightweight data packet of the expressway; according to the lightweight data packet, cloud storage data of the expressway is generated, and a traffic mode of the expressway is analyzed; identifying a traffic flow change trend and an abnormal traffic condition of the expressway, and setting an abnormity self-service processing mechanism and an intelligent auxiliary system of the expressway; defining a traffic management mode and a user interaction mechanism of the expressway, and generating a data sharing platform of the expressway; and in combination with the whole-region road sensing network, the traffic flow change trend and the data sharing platform, traffic prediction processing of the expressway is executed, and a prediction processing result is obtained. According to the invention, the prediction efficiency and accuracy of the expressway traffic prediction system can be improved.

The invention discloses a data processing method and device based on edge computing, equipment and a storage medium, and belongs to the technical field of big data. According to the method, firstly, features are extracted from initial data collected by a sensor through feature extraction, and the data type is identified through data classification; then, according to the data type, distributing the data to a corresponding edge server for preprocessing, and generating an edge processing result; then, in an exception handling decision library of the edge server, a target decision conforming to the processing result is searched, and the decision is executed to generate a final data processing result. And finally, uploading an edge processing result and a final data processing result to a cloud server for storage. The invention further relates to the technical field of block chains, and the initial data is stored on a block chain network. The data transmission pressure can be reduced, the data processing efficiency can be improved, and the response speed and the intelligent level of the system can be enhanced.

The embodiment of the invention provides a secret key generation method and unit, an acceleration unit, electronic equipment and a storage medium, the secret key generation method is used for generating a rotation secret key required for performing noise reduction processing on a ciphertext to be subjected to noise reduction, and the method comprises the following steps: reading a plurality of fault-tolerant learning ciphertexts generated according to the ciphertext to be subjected to noise reduction, the to-be-denoised ciphertext is obtained based on a ciphertext output by a fully homomorphic encryption function; reading a bootstrap key according to the number of rounds of denoising processing on the ciphertext to be denoised; according to the plurality of fault-tolerant learning ciphertexts, respectively shifting coefficients of a plurality of polynomials included in the bootstrap key to obtain a plurality of rotating keys; and respectively outputting the plurality of rotation keys, so that the plurality of rotation keys are used for carrying out noise reduction processing on the ciphertext to be subjected to noise reduction. According to the scheme, the hardware storage and bandwidth consumption in the ciphertext noise reduction process can be reduced.

The invention discloses an improved PBFT consensus method and terminal, and the method comprises the steps: updating an initial reputation value of a node through a first PBFT consensus algorithm, and selecting a main node; the main node and the consensus node receive transaction information sent by the client and store the transaction information to node memory pools corresponding to the nodes respectively; the consensus node sends a transaction receiving notification to the main node, the main node sends a transaction confirmation message to the consensus node, and if the consensus node does not receive the transaction confirmation message, a transaction confirmation information obtaining request is sent to the main node; otherwise, judging whether transaction information corresponding to the transaction confirmation message exists in a node memory pool of the main node according to the transaction confirmation message, if not, broadcasting a transaction request to the node containing the transaction information to obtain the transaction information, constructing a candidate block by the main node, putting the transaction hash into the candidate block, and sending the transaction hash to the main node; and the broadcast candidate block is consensus through a second PBFT consensus algorithm, so that the bandwidth consumption of the main node is reduced, the block throughput is improved, and the disability possibility of the main node is reduced.

The invention provides a low-latency redundancy communication protocol based on an improved PRP protocol, which is compatible with a PRP protocol standard of IEC 62439-3-2016 and works on a link layer. The dual-redundancy port is connected to an upper-layer protocol through a link redundancy entity and is transparent to the upper-layer protocol; the network end nodes are provided with dual-redundancy or triple-redundancy network ports which are respectively connected to networks which are mutually independent and have the same topological structure, and the networks work in parallel; and the same IP address and MAC address are set for each network port to which the end node supporting the PRP protocol belongs. The method is characterized in that a redundancy discarding algorithm is changed into a mode of directly uploading a first communication frame to an application layer; taking {a source IP address, a source MAC address and a frame sequence number} as a judgment condition of a redundant frame; the method comprises the following steps: writing a single-network-port node IP address in a network into a configuration file in advance in a node by adopting a pre-configuration file mode; and network port link on-off frequency statistics, super receiving window statistics, frame number discontinuous statistics and redundant frame asynchronous frequency statistics are added.

The invention discloses a high-concurrency trusted computing remote certification method and system based on equipment type adaptation, and relates to the technical scheme that the method comprises the following steps: receiving a registration request which is sent by a client and contains an equipment type identifier; creating a thread pool, packaging the received registration request into a registration processing task, scheduling the registration processing task, analyzing an equipment type field in the registration request, and storing a mapping relationship between a client identifier and an equipment type to a local configuration file; in the challenge certification stage, querying the equipment type of the client from the local configuration file, and selecting an adaptive remote certification protocol according to a preset mapping rule; and packaging response verification operation of the server to the client into a proof processing task, and submitting the proof processing task to a thread pool for high-concurrency scheduling. The method can adapt to multi-form client requests, and can efficiently process large-scale concurrent remote attestation requests at the same time.

This application provides a method and system for managing large file caches automatically in a browser, relating to the field of cache management technology. This application intercepts resource requests and generates resource descriptors during the loading of a 3D geographic information scene. Based on browser type, resource type, network caching policy, and storage quota, it determines the automatic caching threshold and target resource data volume to identify resources exceeding the threshold. A scene dependency pool containing necessary resources for the first screen and expected resources for adjacent view areas is generated according to scene dependency identifiers. Resources exceeding the threshold are fragmented and written to the browser database to form shadow cache records. By combining address keys, version verification information, resource-level integrity bitmaps, and fragment-level integrity bitmaps, it performs hit reconstruction, missing data filling, changed fragment replacement, and pool-level eviction. This improves the caching recoverability of large file resources on the browser side, the stability of first-screen loading, version update efficiency, and capacity management accuracy.

A host device, a storage device, and systems and methods thereof are provided. The B-tree-based retrieval method executed by a host device includes: acquiring query information from a memory of a storage device based on a B-tree query request for a table; sending query information to the storage device so as to store the query information in a memory of the storage device; sending a B tree query request to a storage device to start a query for the table in the storage device; a result of the B-tree query request is received from the storage device.

The invention relates to the technical field of communication, and discloses a multicast message processing method and equipment, which are used for improving the load balancing effect and forwarding performance of a multicast message and considering the internal resource occupation of the equipment. The method comprises the following steps: firstly, dividing a multicast message meeting a first preset condition into a logic frame on an uplink card, marking the multicast message based on a serial number of the logic frame to which the multicast message belongs, forwarding the multicast message marked with the serial number to a corresponding switching network card, and then switching the multicast message with the serial number on the switching network card. According to the number N of downlink line cards contained in a multicast group to which the multicast messages belong, the multicast messages are copied to obtain N parts of multicast messages, the N parts of multicast messages are forwarded to the corresponding downlink line cards, and finally, on the downlink line cards, the multicast messages are reordered according to the sequence of serial numbers of logic frames to which the multicast messages belong. And forwarding the reordered multicast message to a network.

The invention discloses a distributed detection method and system for SDN abnormal traffic based on D-VAE-WGAN, and the method comprises the steps: carrying out the cooperative training of a D-VAE-WGAN model based on a collected original traffic sample data set, and obtaining an optimal D-VAE-WGAN model; the cloud server sends a copy of the trained discriminator Dd to each subnet controller, and the copy of the trained discriminator Dd, an original encoder Ge, an original decoder Gd and an original discriminator De in the controller form a detection agent; calculating a reconstruction error and a discrimination error of the reconstructed sample based on the detection agent, and obtaining an error value of the sample; and judging based on the obtained error value of the sample and a set threshold value, and if the error value is greater than the judged threshold value, judging that the sample is an abnormal sample. According to the method, the problem of slow convergence of the GAN is solved by taking the VAE as an encoder, and the risk of'mode collapse 'of the GAN is avoided by taking the Wasserstein distance as similarity measurement. Joint training is carried out by using a generator to exchange parameters, so that each sub-network can learn flow data distribution in other sub-networks, and the overall defense capability of the SDN network is improved.

The application provides a kind of transmission layer data packet management method based on fragmentation and reorganization, belong to computer network technical field.Each device includes a server and multiple clients;The process of the first device transmitting messages to the second device is as follows: multiple clients of the first device transmit messages to a sending queue;The server of the first device monitors the sending queue, fragments the message data packet to obtain multiple sub-packets;The server of the second device receives the sub-packets sent by the server of the first device, reassembles the sub-packets, and sends them to a receiving queue;The clients of the second device block and wait for messages from the receiving queue, filter messages by analyzing the identity field in the message header, and process data packets that match their own identity.This method dynamically adjusts the packet size based on the network environment state, avoiding the packet loss or truncation problem caused by MTU limitation on high latency links in the traditional fixed packet mode.

The embodiment of the invention provides an image display processing method and device and a storage medium, and belongs to the technical field of image processing. The method comprises the steps of determining row boundary coordinates of each row of pixels in each target rectangular image displayed in a preset canvas; according to the row boundary coordinates of the target rectangular images in the same row, target pixel segments formed by mutual segmentation of the target rectangular images are determined; generating an image request message according to each target pixel segment, and sending the image request message to a preset memory through a preset bus; receiving target image data of the memory in response to the image request message; and updating uncovered pixels in each target rectangular image in the canvas according to the target image data. The device and the storage medium can realize the method. The embodiment of the invention can give consideration to the image display effect while reducing the hardware resource consumption of the device and the bandwidth consumption of the hardware system of the device.

This disclosure relates to the field of semiconductor technology, providing a semiconductor device to address the technical problem that high-bandwidth memory technology still has significant room for improvement. The semiconductor device includes a chip stack structure, comprising: a first semiconductor chip and a second semiconductor chip stack structure stacked along a first direction; the first semiconductor chip includes a controller, a computing module, and an interface module; the controller is configured to: perform a first access operation on stored data in the second semiconductor chip stack structure and send the stored data to the interface module to allow external devices to access the stored data in the second semiconductor chip stack structure through the interface module; and perform a second access operation on the stored data in the second semiconductor chip stack structure and send the stored data to the computing module to allow the computing module to perform computational operations on the stored data. This improves integration and shortens data transmission paths, reducing bandwidth consumption and energy loss.

The invention discloses an auto-regression and mask diffusion double-normal-form fusion language model hardware acceleration system based on an FPGA (Field Programmable Gate Array), and relates to the field of FPGA and machine learning. The invention provides a model core calculation process-oriented hardware acceleration architecture by aiming at a language model fusing double normal forms of an autoregression model and a mask diffusion model and adopting the characteristics of revising an attention mechanism and parallel generation of a KV cache. The method disclosed by the invention is implemented by taking an Eso-LMs (Esolic Language Models) model as an example. The system comprises a layer normalization and adaptive layer normalization modulation module, a QKV projection module, a rotation position coding application module, a KV cache management module, a multi-head attention calculation module, an output projection and residual connection module and a multi-layer perceptron module. By optimizing the calculation sequence and the data flow of each module in the model calculation process and adopting the pipeline parallel and resource reuse technology, the efficient reasoning acceleration of the language model fusing the autoregression and mask diffusion double normal forms on the FPGA platform is realized, and the model reasoning speed is obviously improved. According to the system, the advantage of FPGA customizable hardware acceleration is fully exerted, the utilization efficiency of hardware resources is improved, data pipeline blockage is eliminated, calculation delay and storage overhead are reduced by reconstructing the data flow direction and constructing a whole-process pipeline processing architecture, and the system is suitable for the deployment requirement of an edge calculation scene.

The present invention proposes a processor with pipeline processing design and an execution path prediction method. The processor with pipeline processing design includes a memory controller, an instruction cache module, a sending unit, a scheduler and an execution unit; the execution path prediction method includes: taking the execution of the instruction as the predicted satisfied condition of the conditional jump; when the instruction with a jump request is read, detecting whether the satisfied condition of the conditional jump corresponding to the conditional jump prediction instruction occurs; when the satisfied condition of the conditional jump does not occur, the pipeline continues to execute the next instruction; when the satisfied condition of the conditional jump occurs, the program pointer moves to the specified position requested by the satisfied conditional jump instruction, and the pipeline continues to execute the instruction from the specified position requested by the conditional jump instruction. The present invention can reduce the effect loss due to incorrect prediction by designing the cache column with a jump address, thereby improving the execution efficiency of the program.

The application relates to the field of power system data acquisition and edge computing, and discloses a multi-source heterogeneous data pre-acquisition and edge intelligent processing method, which comprises the following steps: using a modal division mechanism, combining the operation state of power equipment, and performing condition correction on an adaptive sampling frequency to obtain a corrected sampling frequency, so as to acquire multi-source heterogeneous data; extracting fusion core features from multi-dimensional feature vectors; substituting the fusion core features into a general fault judgment model and a time sequence prediction model to respectively output equipment fault prediction results and time sequence prediction results, and obtaining early warning information; based on the fusion core features, the early warning information and the equipment fault prediction results of each acquisition node, and combined with the Lymerzi complexity theory, the spatio-temporal coupling law is identified; and based on the spatio-temporal coupling law and the time sequence prediction results, edge end decision suggestions are provided for source-grid-load-storage collaborative regulation. The application effectively improves the power system data processing efficiency and the power grid operation and maintenance regulation level.

The present invention provides a method and computing device for artificial intelligence computing optimization, the method comprising: the main processor calculates the amount of memory occupied by control information, the control information comprising the control information of the first operator and the control information of the second operator; the main processor determines that the amount of memory occupied by the control information is greater than the memory amount of a single tightly coupled cache, then the main processor copies the control information of the first operator to the first tightly coupled cache of the slave processor, so that the slave processor enables the intelligent computing engine to perform operations using the control information. According to the technical solution of the present invention, it is possible to reduce the memory space occupied by data, reduce communication time, and improve computing efficiency and hardware resource utilization.

The invention discloses a live video downloading method and a related device, relates to the technical field of software, is applied to a P2P (Peer-to-Peer) scheduling server, and is used for acquiring a substream configuration of a target live stream, and the substream configuration is used for describing a substream room corresponding to the target live stream; allocating a first substream room to the P2P node of the video to be downloaded based on the substream configuration, and determining a node role of the P2P node in the first substream room; the substream configuration is sent to the P2P node, so that the P2P node determines a second substream room corresponding to a video slice to be downloaded, and the video slice is a logic slice divided by the CDN for a video file of the target live broadcast stream; and in response to a scheduling request for the second sub-stream room sent by the P2P node, recommending a downloading mode with the optimal performance corresponding to the second sub-stream room to the P2P node based on the node role, so that the P2P node downloads the video slices based on the downloading mode and forms a video file. According to the invention, the downloading speed of the live video can be improved to the greatest extent, and the live bandwidth of the CDN is saved.

This invention proposes a wearable device interaction method and apparatus, and a computer device based on memory information. The method includes: collecting multimodal raw data through a wearable device; performing event recognition and semantic extraction on the raw data of each modality, and outputting a single-modal semantic description; comprehensively analyzing all single-modal semantic descriptions within the same time period to generate an event chain and event context description; saving an event table, an association information table, and an index table to a database, wherein the event table stores the event chain and event context description, the association information table stores the relationships between events, and the index table establishes a data retrieval channel; automatically generating reminder tasks based on the data in the event table, association information table, and index table, and pushing them to the user when the task triggering conditions are met, wherein the task triggering conditions include at least one of time, location, scenario, and unfinished tasks. This invention achieves efficient and accurate active and passive intelligent interaction, improving user experience and system efficiency.

This invention discloses a personnel behavior recognition and early warning system for specific areas of a power plant, relating to the field of intelligent industrial safety monitoring technology. It includes a data acquisition module, an edge computing module, and a central processing platform. The data acquisition module is responsible for collecting and initially processing multi-source heterogeneous data, including personnel identity, behavior, location, and environmental parameters. The edge computing module performs lightweight processing and localized decision-making on the raw data, reducing the load on the central processing platform. The central processing platform achieves full-process safety control of high-risk areas through multimodal data fusion, dynamic access control, and trajectory analysis. In this invention, lightweight AI models are embedded in various cameras of the employee badge authentication terminal and visual perception unit, enabling preliminary inference to be performed directly on the employee badge authentication terminal and camera, thus equipping the employee badge authentication terminal and camera with edge computing capabilities. Independent edge servers or industrial control computers are deployed near the data sources in various areas of the power plant as regional edge computing nodes.

This invention discloses an adaptive data acquisition, signing, and encapsulation method and system for the Internet of Things (IoT). The method includes: dynamically determining a batch signing threshold based on environmental parameters; acquiring data in real time, calculating and caching hash values, and encapsulating the data and its corresponding hash values ​​into data packets for transmission to the cloud; when the number of transmitted data packets reaches the batch signing threshold, triggering a signing operation, generating an overall digital signature for all cached hash values ​​using a built-in private key, and encapsulating the set of all hash values ​​and the overall digital signature into a signature packet for transmission to the cloud for cloud verification of data integrity and batch confirmation of data packet authenticity. This invention changes the traditional strongly bound encapsulation mode of "data + signature," separating the data packets and signature packets into separate encapsulations, changing the traditional "signature for every packet" to "acquisition and transmission as needed, batch signing," greatly reducing the frequency of asymmetric encryption by hardware security chips, eliminating transmission congestion caused by encryption, and significantly increasing system throughput.

The invention discloses a multi-target detection method based on task driving, and the method comprises the steps: S1, building a data set, and carrying out the preprocessing: collecting image data of a to-be-detected and monitored region according to a target detection task, carrying out the marking of the obtained image data, making a data set, and carrying out the preprocessing of the data set; s2, constructing and training a multi-target detection model: constructing a multi-target detection network, and training the model by using a data set; S3, detecting and verifying: locally deploying the multi-target detection model, accessing multiple paths of real-time video streams into the multi-target detection model for multi-target detection, and judging whether a target exists in a monitoring area or not; and comparing and analyzing a multi-channel video stream pushing result with a polling algorithm pushing result, and outputting a final result. According to the method, a UIB module lightweight algorithm and a polling algorithm are combined to save bandwidth consumption, and a PIOUv2 loss function is combined to improve detection precision, accuracy, real-time performance and adaptability under the condition of limited hardware and limited bandwidth.

The invention discloses an enterprise-based data outbound system, which belongs to the technical field of data transmission, and comprises a data outbound capability layer, and the data outbound capability layer comprises the following modules: a compliance auditing module, which is used for carrying out compliance check on cross-border data flow to ensure that data transmission meets regulatory requirements of a target country or region, the security guarantee module is used for guaranteeing the security and transparency of the data in the cross-border transmission process, and the data flow optimization module is used for optimizing the data flow based on real-time network conditions, regulation requirements and data transmission efficiency factors. According to the invention, automatic compliance review and multiple security protection of cross-border data flow are realized, and the risk of violation of an enterprise is remarkably reduced. Through intelligent routing optimization and edge calculation, the transmission efficiency is effectively improved, and delay and bandwidth consumption are reduced. The architecture can be seamlessly integrated with an existing enterprise framework, has good compatibility and expansibility, and supports an enterprise to realize safe, compliant and efficient data flow management in a global range.

The invention provides a data transmission method of a multi-link data transmission terminal, which comprises the following steps that the following steps are carried out in sequence; the method comprises the following steps: step 1, acquiring all networks selected by a mobile phone terminal, acquiring the type of each network, and creating a socket according to the network type; 2, the number of sockets is created according to the number of the networks obtained in the step 1, all the sockets are in one-to-one correspondence with the networks, and each socket is connected with the corresponding network; a network is divided into a wired network and a wireless network, and the wired network and the wireless network are processed by different threads; for a wired network, acquiring an ip and a port of the wired network, and creating a socket and a connection network according to the ip and the port; the method comprises the following steps: for a wireless network, acquiring network ip and ports respectively according to access point names of Wifi and 2G, 3G and 4G cellular networks, and establishing a socket connection network according to respective ip and port; and step 3, after each socket is created, periodically sending a heartbeat packet to the server for detecting whether each network is unobstructed or not.

The application discloses a substation intelligent patrol single-mode and multi-mode model hierarchical collaborative identification method and system. The method comprises the following steps: obtaining substation intelligent patrol data of multiple data types, adding meta information to each type of substation intelligent patrol data to obtain multi-modal data; preprocessing the multi-modal data and performing preliminary defect detection through a lightweight model to generate a category probability vector and a candidate defect set, determine a modal confidence and a preliminary category to obtain a first identification result; determining whether the first identification result needs further analysis according to a set hierarchical trigger strategy; if yes, performing cross-modal feature fusion and joint verification on the first identification result to obtain a second identification result; obtaining a final defect identification conclusion through probability logic reasoning and providing a detailed reasoning explanation. Through the method of the application, the defect identification reliability is improved while meeting the real-time and bandwidth constraints, and the reasoning explanation is output.

This application relates to a method and system for comparing table data in a row-oriented storage database. The method includes: acquiring the database to be verified; collecting business characteristics, constructing a B+ tree index, and partitioning the database; sequentially locating the difference partitions, difference rows, and difference fields based on the B+ tree index and partitioning combined with hash calculation; and outputting the comparison results based on the difference fields. This embodiment achieves rapid location and on-demand reading of difference partitions in a row-oriented storage database. By sequentially locating the difference partitions, difference rows, and difference fields based on the B+ tree index and partitioning combined with hash calculation, it achieves rapid identification of the partitions containing the difference data, avoiding a full scan of irrelevant data, thereby significantly reducing disk I / O, memory usage, and bandwidth consumption, improving verification efficiency, and reducing resource overhead.

The specification provides a certificate identification method and a computing device, the method comprising: collecting multiple frames of images containing a certificate at a client; inputting the multiple frames of images into a video super-resolution (VSR) model to obtain a synthesized image; selecting several target images from the multiple frames of images; sending the synthesized image and the target images to a server; performing optical character recognition (OCR) on the synthesized image and performing anti-forgery detection on the target images at the server; and obtaining a certificate identification result according to the OCR recognition result and the anti-forgery detection result. The method uses a high-quality super-resolution synthesized image for OCR recognition and a target image retaining original image features for anti-forgery detection through a double-track uploading strategy, fundamentally solving the contradiction between identification and anti-forgery. In addition, the method completes the super-resolution synthesis task with the largest amount of calculation at the client, reducing the computing pressure of the server.

The invention provides a convolutional neural network inference method based on a core grain architecture, and the method comprises the steps: S1, obtaining to-be-processed data and a pre-trained convolutional neural network, and S2, distributing a mapping region for each network layer in the core grain architecture according to a graph division strategy; s3, segmenting the feature map and the weight tensor corresponding to each network layer into a plurality of feature blocks and a plurality of weight blocks, and sequentially distributing the plurality of weight blocks corresponding to each network layer to a plurality of calculation units in the corresponding mapping area, determining a loading sequence of transmitting each feature block corresponding to each network layer to different computing units in the corresponding mapping region to obtain an initial mapping scheme of the convolutional neural network; s4, performing multi-round iteration on the initial mapping scheme to obtain a target mapping scheme; and S5, based on the target mapping scheme, loading the convolutional neural network to a calculation unit corresponding to the core particle architecture to realize reasoning of the to-be-processed data.

The invention provides a global sequence establishing method and device, electronic equipment and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: acquiring a first access transaction of a first access object for a target accessed object; determining a relationship between the first access transaction and a second access transaction according to first transaction information of the first access transaction, an object type of the target accessed object and second transaction information of the second access transaction of the target accessed object; and when the first access transaction and the second access transaction do not have the dependency relationship, not establishing a global order of the target accessed object for the first access transaction. According to the method and the device, a global sequence is not established for all the obtained access transactions, but based on the relationship between the access transaction and the latest access transaction, the global sequence is not established for the access transaction without a dependency relationship, so that the establishment of unnecessary global sequences is reduced, and the processing time of the access transaction is shortened.